Check for Masked elements in NumPy Masked array
NumPy: Masked Arrays Exercise-20 with Solution
Write a NumPy program that creates a masked array and checks if any masked elements are present.
Sample Solution:
Python Code:
import numpy as np
import numpy.ma as ma
# Create a 2D NumPy array of shape (5, 5) with random integers
array_2d = np.random.randint(0, 100, size=(5, 5))
# Define a condition to mask elements less than 20
condition = array_2d < 20
# Create a masked array from the 2D array using the condition
masked_array = ma.masked_array(array_2d, mask=condition)
# Check if any masked elements are present
has_masked_elements = masked_array.mask.any()
# Print the original array, the masked array, and whether any masked elements are present
print('Original 2D array:\n', array_2d)
print('Masked array (values < 20 are masked):\n', masked_array)
print('Any masked elements present?:', has_masked_elements)
Output:
Original 2D array: [[52 75 32 47 50] [39 1 45 63 62] [95 36 75 41 10] [40 59 51 76 11] [48 27 33 88 94]] Masked array (values < 20 are masked): [[52 75 32 47 50] [39 -- 45 63 62] [95 36 75 41 --] [40 59 51 76 --] [48 27 33 88 94]] Any masked elements present?: True
Explanation:
- Import Libraries:
- Imported numpy as "np" for array creation and manipulation.
- Imported numpy.ma as "ma" for creating and working with masked arrays.
- Create 2D NumPy Array:
- Create a 2D NumPy array named array_2d with random integers ranging from 0 to 99 and a shape of (5, 5).
- Define Condition:
- Define a condition to mask elements in the array that are less than 20.
- Create Masked Array:
- Create a masked array from the 2D array using ma.masked_array, applying the condition as the mask. Elements less than 20 are masked.
- Check for Masked Elements:
- Check if any masked elements are present in the masked array using the any method on the mask attribute.
- Finally print the original 2D array, the masked array, and whether any masked elements are present.
Python-Numpy Code Editor: